Displaying 10 of 207 results for "Chantal van Esch" clear search
I am an environmental archaeologist, specializing in charcoal analysis, computational and analytical proxy modeling, and quantitative methods to understand the dynamic relationship between fire, humans, and long-term environmental change. I work primarily in the Western United States and the Western Mediterranean. I am passionate about our public lands and ensuring that everyone has access and opportunity to experience them.
Envrionmental Archaeology, Fire Ecology, GIS, Agent-based modeling, Geoarchaeology
Dr. Aaron Bramson is principal investigator of the AI Strategy Center of GA technologies in Tokyo, Japan, as well as an Affiliate Researcher in the Department of General Economics of Ghent University in Belgium. His research specialty is complexity science, especially methodologies for modeling complex systems. Research topics span across disciplines: measures of polarization and diversity, belief measure interoperability, integrating geospatial and network analyses for measuring walkability and neighborhood identification, and myriad applications in artificial intelligence and data visualization. He received his Ph.D. from the University of Michigan in a joint program with the departments of Political Science and Philosophy as well as an M.S. in Mathematics from Northeastern University.
Complex systems, agent-based modeling, social simulation, computational models, network models, network theory, methodology, philosophy of science, ontology, epistemology, ethics, artificial intelligence, big data analysis, geospatial data analysis,
Smarzhevskiy Ivan, born 1961, graduated from the Faculty of Mechanics and Mathematics of Moscow State University in 1983. Ph.D. in Economic Sciences since 2000.
Research interests: individual and collective behavior in the organization, decision making, sociology of small groups.
decision making, sociology of small groups, agent based models
Volker Grimm currently works at the Department of Ecological Modelling, Helmholtz-Zentrum für Umweltforschung. Volker does research in ecology and biodiversity research.
How to model it: Ecological models, in particular simulation models, often seem to be formulated ad hoc and only poorly analysed. I am therefore interested in strategies and methods for making ecological modelling more coherent and efficient. The ultimate aim is to develop preditive models that provide mechanstic understanding of ecological systems and that are transparent and structurally realistic enough to support environmental decision making.
Pattern-oriented modelling: This is a general strategy of using multiple patterns observed in real systems as multiple criteria for chosing model structure, selecting among alternative submodels, and inversely determining entire sets of unknown model parameters.
Individual-based and agent-based modelling: For many, if not most, ecological questions individual-level aspects can be decisive for explaining system-level behavior. IBM/ABMs allow to represent individual heterogeneity, local interactions, and/or adaptive behaviour
Ecological theory and concepts: I am particularly interested in exploring stability properties like resilience and persistence.
Modelling for ecological applications: Pattern-oriented modelling allows to develop structurally realistic models, which can be used to support decision making and the management of biodiversity and natural resources. Currently, I am involved in the EU project CREAM, where a suite of population models is developed for pesticide risk assessment.
Standards for model communication and formulation: In 2006, we published a general protocol for describing individual- and agent-based models, called the ODD protocol (Overview, Design concepts, details). ODD turned out to be more useful (and needed) than we expected.
Applying agent-based models to archaeological data, using modern ethnoarchaeological data as an analog for behavior.
Modeling land use change from smallholder agricultural intensification
Agricultural expansion in the rural tropics brings much needed economic and social development in developing countries. On the other hand, agricultural development can result in the clearing of biologically-diverse and carbon-rich forests. To achieve both development and conservation objectives, many government policies and initiatives support agricultural intensification, especially in smallholdings, as a way to increase crop production without expanding farmlands. However, little is understood regarding how different smallholders might respond to such investments for yield intensification. It is also unclear what factors might influence a smallholder’s land-use decision making process. In this proposed research, I will use a bottom-up approach to evaluate whether investments in yield intensification for smallholder farmers would really translate to sustainable land use in Indonesia. I will do so by combining socioeconomic and GIS data in an agent-based model (Land-Use Dynamic Simulator multi-agent simulation model). The outputs of my research will provide decision makers with new and contextualized information to assist them in designing agricultural policies to suit varying socioeconomic, geographic and environmental contexts.
Water scarcity generated by climate change and mismanagement, affects individual at microlevel and the society and the system at a more general level. The research focuses on irrigation system and their robustness and adaptation capacity to uncertainty. In particular it investigates the evolution of farmers interactions and the effectiveness of policies by means of dynamic game theory and incorporate the results into an Agent Based Model to explore farmers emergent behaviors and the role of an agency in defining policies. Early knowledge of individual decision makers could help the agency to design more acceptable solutions.
Sae Schatz, Ph.D., is an applied human–systems researcher, professional facilitator, and cognitive scientist. Her work focuses on human–systems integration (HSI), with an emphasis on human cognition and learning, instructional technologies, adaptive systems, human performance assessment, and modeling and simulation (M&S). Frequently, her work seeks to enhance individual’s higher-order cognitive skills (i.e., the mental, emotional, and relational skills associated with “cognitive readiness”).
The goal of my research program is to improve our understanding about highly integrated natural and human processes. Within the context of Land-System Science, I seek to understand how natural and human systems interact through feedback mechanisms and affect land management choices among humans and ecosystem (e.g., carbon storage) and biophysical processes (e.g., erosion) in natural systems. One component of this program involves finding novel methods for data collection (e.g., unmanned aerial vehicles) that can be used to calibrate and validate models of natural systems at the resolution of decision makers. Another component of this program involves the design and construction of agent-based models to formalize our understanding of human decisions and their interaction with their environment in computer code. The most exciting, and remaining part, is coupling these two components together so that we may not only quantify the impact of representing their coupling, but more importantly to assess the impacts of changing climate, technology, and policy on human well-being, patterns of land use and land management, and ecological and biophysical aspects of our environment.
To achieve this overarching goal, my students and I conduct fieldwork that involves the use of state-of-the-art unmanned aerial vehicles (UAVs) in combination with ground-based light detection and ranging (LiDAR) equipment, RTK global positioning system (GPS) receivers, weather and soil sensors, and a host of different types of manual measurements. We bring these data together to make methodological advancements and benchmark novel equipment to justify its use in the calibration and validation of models of natural and human processes. By conducting fieldwork at high spatial resolutions (e.g., parcel level) we are able to couple our representation of natural system processes at the scale at which human actors make decisions and improve our understanding about how they react to changes and affect our environment.
land use; land management; agricultural systems; ecosystem function; carbon; remote sensing; field measurements; unmanned aerial vehicle; human decision-making; erosion, hydrological, and agent-based modelling
Displaying 10 of 207 results for "Chantal van Esch" clear search